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The most commonly used statistical measure of variation.
Consists of editing, coding, data entry, and data cleaning.
The value or category in a distribution with the highest frequency.
Replacing missing values in data analysis by estimating values from the available data.
Examples are Cramer’s phi and the correlation coefficient.
The numerical difference between an observed value and the value predicted by the regression line.
Indicates how much the dependent variable changes for every one-unit increase in the independent variable.
Graphic depiction of a bivariate distribution.
Documentation for a data file that usually contains the question wording and responses codes for each variable.
Detecting and resolving errors in coding and data entry.
The middle value in a distribution.
A graphic display of a univariate distribution.